Image sequences are used in a wide variety of applications such as satellite imaging, video communications, target tracking, automated object recognition, medical imaging and the like. In each application there is always some inherent noise present that corrupts the quality of the image sequence. The noise is unavoidably created as the image sequence is transmitted, recorded, viewed or otherwise processed. The artifacts caused by noise adversely affect every application that utilizes image sequence. For examples of how noise affects various image sequence applications, consider the following diverse applications. In satellite imaging, noise affects the resolution of the recorded images, as such noise may wash out the details of an image when the image is magnified. In video communications, noise may make an image seem blurred or out of focus to a viewer. In applications such as target tracking, the presence of noise limits the robustness of low-level visual operations, limiting the operating parameters of certain target tracking systems. Finally, in medical applications, such as X-ray fluoroscopy, the amount of noise present in the image sequence is inversely proportional to the dosage of the X-ray radiation being used. Consequently, if the amount of noise were suppressed, lower dosages of X-rays could be used.
As can be seen from the above examples, it is highly desirable to limit the amount of noise found within an image sequence. Prior art noise reduction techniques for image-sequences often use motion-compensated temporal smoothing. Temporal smoothing is performed by a low-pass filter that reduces the statistical variance of the noise. However, temporal low-pass filtering has a tendency to blur the edges of a moving image. Motion compensation is commonly used to preserve moving regions during temporal smoothing. For this purpose, the image-motion field is computed in advance for each of the frames involved in the temporal filtering. The images are then corrected using the motion field. If the image-motion field is accurate, the resulting images will not have any significant inter-frame motion, and the temporal filtering does not introduce any substantial blurring. Such motion compensation requires that extremely accurate motion fields be computed in advance. It is understood that robust and accurate real-time computation of image-motion requires a sophisticated program and a powerful, fast computer. For this reason, motion-compensated temporal smoothing is both a computationally inefficient and expensive technique. Additionally, the accurate calculating of a motion field is dependent upon its input data. If a noisy image sequence is the only input, there are theoretical limits on the accuracy of the motion field that can be computed. Because of this limit on accuracy and the computing time need to create motion fields, motion-compensated temporal smoothing has limited applicability to high noise, real-time applications, such as target tracking, X-ray fluoroscopy, etc.
Prior art motion compensation techniques for image sequence that require the computation of a motion field are exemplified in U.S. Pat. Nos. 4,727,422 to Hinman, and 4,717,956 to Moorehead et al, and European Patent Nos. 318,121A1 to Haghiri and 154,126A2 to Mussman.
Prior art references that specifically distinguish between moving and stationary objects in an image sequence are exemplified in European Patent Nos. 414,017A2 to Stiller, 385,384A2 to Karmann et al and a paper from the 6th Scandinavian Conference on Image Analysis Proceeding entitled "Detection and Tracking of Moving Objects by Adaptive Background Extraction" by Karmann et al. Finally, a technique for recursively interpolating image sequences to reduce temporal aliasing is disclosed in European Patent No. 390,660 to Phillipe et al.
The disclosed prior art techniques use motion compensation for either filtering or coding of image sequences. As such, each of the prior art techniques is computationally burdensome and inefficient. It is therefore a primary objective of the present invention to set forth a motion compensated enhancement apparatus and technique that does not compute motion and, as such, offers a reduction in the computational burden of processing an image sequence.